Pandas Profiling Report

Dataset statistics

Number of variables	15
Number of observations	459
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	328.7 KiB
Average record size in memory	733.3 B

Variable types

Text	6
Categorical	4
Numeric	5

Alerts

`attributes_similarity` is highly overall correlated with `similarity_media` and 1 other fields	High correlation
`expected_intent` is highly overall correlated with `find_intent` and 1 other fields	High correlation
`filters_similarity` is highly overall correlated with `similarity_media`	High correlation
`find_intent` is highly overall correlated with `expected_intent` and 1 other fields	High correlation
`intent_similarity` is highly overall correlated with `similarity_media`	High correlation
`similarity_media` is highly overall correlated with `attributes_similarity` and 2 other fields	High correlation
`total_attributes` is highly overall correlated with `attributes_similarity` and 2 other fields	High correlation
`intent_similarity` is highly imbalanced (83.5%)	Imbalance
`user_msg` has unique values	Unique
`total_attributes` has 109 (23.7%) zeros	Zeros
`entity_similarity` has 12 (2.6%) zeros	Zeros

Reproduction

Analysis started	2025-01-30 19:25:44.799310
Analysis finished	2025-01-30 19:25:47.888948
Duration	3.09 seconds
Software version	ydata-profiling vv4.12.2
Download configuration	config.json

user_msg
Text

Unique

Distinct	459
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	50.6 KiB

Length

Max length	281
Median length	97
Mean length	47.592593
Min length	8

Characters and Unicode

Total characters	21845
Distinct characters	71
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	459 ?
Unique (%)	100.0%

Sample

1st row	add student with name=anderson martins gomes, age=20
2nd row	add subject with name=brazilian history, description=the history of brazil
3rd row	add teacher with name=paulo henrique, age=65, email=ph@uece.br
4th row	add subject with name=math, description=the best subject ever
5th row	add subject with name=math, description='the best subject ever!'

Value	Count	Frequency (%)
with	289	8.9%
the	153	4.7%
add	151	4.7%
article	121	3.7%
update	96	3.0%
setting	75	2.3%
show	74	2.3%
a	74	2.3%
name	74	2.3%
and	73	2.3%
Other values (612)	2050	63.5%

Most occurring characters

Value	Count	Frequency (%)
	2768	12.7%
e	2270	10.4%
t	1975	9.0%
a	1711	7.8%
i	1248	5.7%
n	1109	5.1%
d	1002	4.6%
r	940	4.3%
s	913	4.2%
o	834	3.8%
Other values (61)	7075	32.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	21845	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	2768	12.7%
e	2270	10.4%
t	1975	9.0%
a	1711	7.8%
i	1248	5.7%
n	1109	5.1%
d	1002	4.6%
r	940	4.3%
s	913	4.2%
o	834	3.8%
Other values (61)	7075	32.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	21845	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	2768	12.7%
e	2270	10.4%
t	1975	9.0%
a	1711	7.8%
i	1248	5.7%
n	1109	5.1%
d	1002	4.6%
r	940	4.3%
s	913	4.2%
o	834	3.8%
Other values (61)	7075	32.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	21845	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	2768	12.7%
e	2270	10.4%
t	1975	9.0%
a	1711	7.8%
i	1248	5.7%
n	1109	5.1%
d	1002	4.6%
r	940	4.3%
s	913	4.2%
o	834	3.8%
Other values (61)	7075	32.4%

expected_intent
Categorical

High correlation

Distinct	4
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	28.1 KiB

CREATE	169
READ	143
UPDATE	99
DELETE	48

Length

Max length	6
Median length	6
Mean length	5.3769063
Min length	4

Characters and Unicode

Total characters	2468
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CREATE
2nd row	CREATE
3rd row	CREATE
4th row	CREATE
5th row	CREATE

Common Values

Value	Count	Frequency (%)
CREATE	169	36.8%
READ	143	31.2%
UPDATE	99	21.6%
DELETE	48	10.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
create	169	36.8%
read	143	31.2%
update	99	21.6%
delete	48	10.5%

Most occurring characters

Value	Count	Frequency (%)
E	724	29.3%
A	411	16.7%
T	316	12.8%
R	312	12.6%
D	290	11.8%
C	169	6.8%
U	99	4.0%
P	99	4.0%
L	48	1.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2468	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	724	29.3%
A	411	16.7%
T	316	12.8%
R	312	12.6%
D	290	11.8%
C	169	6.8%
U	99	4.0%
P	99	4.0%
L	48	1.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2468	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	724	29.3%
A	411	16.7%
T	316	12.8%
R	312	12.6%
D	290	11.8%
C	169	6.8%
U	99	4.0%
P	99	4.0%
L	48	1.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2468	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	724	29.3%
A	411	16.7%
T	316	12.8%
R	312	12.6%
D	290	11.8%
C	169	6.8%
U	99	4.0%
P	99	4.0%
L	48	1.9%

expected_class
Categorical

Distinct	38
Distinct (%)	8.3%
Missing	0
Missing (%)	0.0%
Memory size	28.6 KiB

article	149
student	109
pokemon	30
city	25
film	24
Other values (33)	122

Length

Max length	14
Median length	7
Mean length	6.5555556
Min length	3

Characters and Unicode

Total characters	3009
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11 ?
Unique (%)	2.4%

Sample

1st row	student
2nd row	subject
3rd row	teacher
4th row	subject
5th row	subject

Common Values

Value	Count	Frequency (%)
article	149	32.5%
student	109	23.7%
pokemon	30	6.5%
city	25	5.4%
film	24	5.2%
company	18	3.9%
subject	17	3.7%
show	15	3.3%
teacher	7	1.5%
elf	6	1.3%
Other values (28)	59	12.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
article	149	32.5%
student	109	23.7%
pokemon	30	6.5%
city	25	5.4%
film	24	5.2%
company	18	3.9%
subject	17	3.7%
show	15	3.3%
teacher	7	1.5%
elf	6	1.3%
Other values (28)	59	12.9%

Most occurring characters

Value	Count	Frequency (%)
t	446	14.8%
e	381	12.7%
c	248	8.2%
i	230	7.6%
a	200	6.6%
l	199	6.6%
r	183	6.1%
n	181	6.0%
s	171	5.7%
u	144	4.8%
Other values (16)	626	20.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3009	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	446	14.8%
e	381	12.7%
c	248	8.2%
i	230	7.6%
a	200	6.6%
l	199	6.6%
r	183	6.1%
n	181	6.0%
s	171	5.7%
u	144	4.8%
Other values (16)	626	20.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3009	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	446	14.8%
e	381	12.7%
c	248	8.2%
i	230	7.6%
a	200	6.6%
l	199	6.6%
r	183	6.1%
n	181	6.0%
s	171	5.7%
u	144	4.8%
Other values (16)	626	20.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3009	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	446	14.8%
e	381	12.7%
c	248	8.2%
i	230	7.6%
a	200	6.6%
l	199	6.6%
r	183	6.1%
n	181	6.0%
s	171	5.7%
u	144	4.8%
Other values (16)	626	20.8%

expected_attributes
Text

Distinct	189
Distinct (%)	41.2%
Missing	0
Missing (%)	0.0%
Memory size	37.4 KiB

Length

Max length	282
Median length	150
Mean length	24.204793
Min length	2

Characters and Unicode

Total characters	11110
Distinct characters	60
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	152 ?
Unique (%)	33.1%

Sample

1st row	{'name': 'anderson martins gomes', 'age': '20'}
2nd row	{'name': 'brazilian history', 'description': 'the history of brazil'}
3rd row	{'name': 'paulo henrique', 'age': '65', 'email': 'ph@uece.br'}
4th row	{'name': 'math', 'description': 'the best subject ever'}
5th row	{'name': 'math', 'description': 'the best subject ever!'}

Value	Count	Frequency (%)
	200	14.3%
name	116	8.3%
title	50	3.6%
year	32	2.3%
author	30	2.1%
age	22	1.6%
the	19	1.4%
a	16	1.1%
raichu	14	1.0%
co_author	14	1.0%
Other values (395)	885	63.3%

Most occurring characters

Value	Count	Frequency (%)
'	1594	14.3%
	939	8.5%
e	875	7.9%
a	764	6.9%
t	535	4.8%
n	534	4.8%
r	532	4.8%
o	466	4.2%
{	459	4.1%
}	459	4.1%
Other values (50)	3953	35.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11110	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	1594	14.3%
	939	8.5%
e	875	7.9%
a	764	6.9%
t	535	4.8%
n	534	4.8%
r	532	4.8%
o	466	4.2%
{	459	4.1%
}	459	4.1%
Other values (50)	3953	35.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11110	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	1594	14.3%
	939	8.5%
e	875	7.9%
a	764	6.9%
t	535	4.8%
n	534	4.8%
r	532	4.8%
o	466	4.2%
{	459	4.1%
}	459	4.1%
Other values (50)	3953	35.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11110	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	1594	14.3%
	939	8.5%
e	875	7.9%
a	764	6.9%
t	535	4.8%
n	534	4.8%
r	532	4.8%
o	466	4.2%
{	459	4.1%
}	459	4.1%
Other values (50)	3953	35.6%

expected_filter_attributes
Text

Distinct	74
Distinct (%)	16.1%
Missing	0
Missing (%)	0.0%
Memory size	29.7 KiB

Length

Max length	89
Median length	2
Mean length	8.6732026
Min length	2

Characters and Unicode

Total characters	3981
Distinct characters	48
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	45 ?
Unique (%)	9.8%

Sample

1st row	{}
2nd row	{}
3rd row	{}
4th row	{}
5th row	{}

Value	Count	Frequency (%)
	275	38.8%
id	76	10.7%
name	73	10.3%
pikachu	16	2.3%
anderson	15	2.1%
1	14	2.0%
8	11	1.6%
year	10	1.4%
11	10	1.4%
4	10	1.4%
Other values (104)	198	28.0%

Most occurring characters

Value	Count	Frequency (%)
'	744	18.7%
{	459	11.5%
}	459	11.5%
	249	6.3%
e	232	5.8%
a	218	5.5%
:	187	4.7%
i	159	4.0%
n	158	4.0%
r	118	3.0%
Other values (38)	998	25.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3981	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	744	18.7%
{	459	11.5%
}	459	11.5%
	249	6.3%
e	232	5.8%
a	218	5.5%
:	187	4.7%
i	159	4.0%
n	158	4.0%
r	118	3.0%
Other values (38)	998	25.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3981	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	744	18.7%
{	459	11.5%
}	459	11.5%
	249	6.3%
e	232	5.8%
a	218	5.5%
:	187	4.7%
i	159	4.0%
n	158	4.0%
r	118	3.0%
Other values (38)	998	25.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3981	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	744	18.7%
{	459	11.5%
}	459	11.5%
	249	6.3%
e	232	5.8%
a	218	5.5%
:	187	4.7%
i	159	4.0%
n	158	4.0%
r	118	3.0%
Other values (38)	998	25.1%

processed_attributes
Text

Distinct	191
Distinct (%)	41.6%
Missing	0
Missing (%)	0.0%
Memory size	42.4 KiB

Length

Max length	677
Median length	2
Mean length	31.699346
Min length	2

Characters and Unicode

Total characters	14550
Distinct characters	65
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	175 ?
Unique (%)	38.1%

Sample

1st row	{'name': 'anderson martins gomes', 'age': '20'}
2nd row	{'name': 'brazilian history', 'history': 'history of'}
3rd row	{'name': 'paulo henrique', 'age': '65', 'email': 'ph@uecebr', '.': 'br'}
4th row	{'name': 'math', 'description': 'the best subject ever'}
5th row	{'name': 'math', 'description': "'the best subject ever!'"}

Value	Count	Frequency (%)
	328	18.4%
name	94	5.3%
title	47	2.6%
author	27	1.5%
a	22	1.2%
the	21	1.2%
measure	20	1.1%
with	19	1.1%
cluster	19	1.1%
age	19	1.1%
Other values (399)	1164	65.4%

Most occurring characters

Value	Count	Frequency (%)
'	1846	12.7%
	1326	9.1%
e	1138	7.8%
a	936	6.4%
t	755	5.2%
n	687	4.7%
r	686	4.7%
o	614	4.2%
i	564	3.9%
"	513	3.5%
Other values (55)	5485	37.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	14550	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	1846	12.7%
	1326	9.1%
e	1138	7.8%
a	936	6.4%
t	755	5.2%
n	687	4.7%
r	686	4.7%
o	614	4.2%
i	564	3.9%
"	513	3.5%
Other values (55)	5485	37.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	14550	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	1846	12.7%
	1326	9.1%
e	1138	7.8%
a	936	6.4%
t	755	5.2%
n	687	4.7%
r	686	4.7%
o	614	4.2%
i	564	3.9%
"	513	3.5%
Other values (55)	5485	37.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	14550	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	1846	12.7%
	1326	9.1%
e	1138	7.8%
a	936	6.4%
t	755	5.2%
n	687	4.7%
r	686	4.7%
o	614	4.2%
i	564	3.9%
"	513	3.5%
Other values (55)	5485	37.7%

processed_filters
Text

Distinct	171
Distinct (%)	37.3%
Missing	0
Missing (%)	0.0%
Memory size	34.7 KiB

Length

Max length	407
Median length	298
Mean length	18.960784
Min length	2

Characters and Unicode

Total characters	8703
Distinct characters	58
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	145 ?
Unique (%)	31.6%

Sample

1st row	{}
2nd row	{}
3rd row	{}
4th row	{}
5th row	{}

Value	Count	Frequency (%)
	299	24.6%
name	97	8.0%
id	76	6.3%
students	40	3.3%
setting	33	2.7%
year	28	2.3%
rosenberg	18	1.5%
with	17	1.4%
author	17	1.4%
the	16	1.3%
Other values (203)	574	47.2%

Most occurring characters

Value	Count	Frequency (%)
'	1398	16.1%
	757	8.7%
e	611	7.0%
a	468	5.4%
{	459	5.3%
}	459	5.3%
t	446	5.1%
r	375	4.3%
n	367	4.2%
:	353	4.1%
Other values (48)	3010	34.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8703	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	1398	16.1%
	757	8.7%
e	611	7.0%
a	468	5.4%
{	459	5.3%
}	459	5.3%
t	446	5.1%
r	375	4.3%
n	367	4.2%
:	353	4.1%
Other values (48)	3010	34.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8703	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	1398	16.1%
	757	8.7%
e	611	7.0%
a	468	5.4%
{	459	5.3%
}	459	5.3%
t	446	5.1%
r	375	4.3%
n	367	4.2%
:	353	4.1%
Other values (48)	3010	34.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8703	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	1398	16.1%
	757	8.7%
e	611	7.0%
a	468	5.4%
{	459	5.3%
}	459	5.3%
t	446	5.1%
r	375	4.3%
n	367	4.2%
:	353	4.1%
Other values (48)	3010	34.6%

find_entity
Text

Distinct	66
Distinct (%)	14.4%
Missing	0
Missing (%)	0.0%
Memory size	28.6 KiB

Length

Max length	45
Median length	7
Mean length	6.4749455
Min length	1

Characters and Unicode

Total characters	2972
Distinct characters	34
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	30 ?
Unique (%)	6.5%

Sample

1st row	student
2nd row	subject
3rd row	teacher
4th row	subject
5th row	subject

Value	Count	Frequency (%)
article	113	24.2%
student	79	17.0%
pokemon	24	5.2%
city	22	4.7%
articles	20	4.3%
students	20	4.3%
film	20	4.3%
subject	17	3.6%
show	15	3.2%
a	12	2.6%
Other values (58)	124	26.6%

Most occurring characters

Value	Count	Frequency (%)
t	429	14.4%
e	375	12.6%
s	237	8.0%
c	225	7.6%
i	223	7.5%
a	208	7.0%
l	183	6.2%
n	172	5.8%
r	164	5.5%
u	136	4.6%
Other values (24)	620	20.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2972	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	429	14.4%
e	375	12.6%
s	237	8.0%
c	225	7.6%
i	223	7.5%
a	208	7.0%
l	183	6.2%
n	172	5.8%
r	164	5.5%
u	136	4.6%
Other values (24)	620	20.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2972	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	429	14.4%
e	375	12.6%
s	237	8.0%
c	225	7.6%
i	223	7.5%
a	208	7.0%
l	183	6.2%
n	172	5.8%
r	164	5.5%
u	136	4.6%
Other values (24)	620	20.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2972	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	429	14.4%
e	375	12.6%
s	237	8.0%
c	225	7.6%
i	223	7.5%
a	208	7.0%
l	183	6.2%
n	172	5.8%
r	164	5.5%
u	136	4.6%
Other values (24)	620	20.9%

find_intent
Categorical

High correlation

Distinct	4
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	28.1 KiB

CREATE	158
READ	136
UPDATE	111
DELETE	54

Length

Max length	6
Median length	6
Mean length	5.4074074
Min length	4

Characters and Unicode

Total characters	2482
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CREATE
2nd row	CREATE
3rd row	CREATE
4th row	CREATE
5th row	CREATE

Common Values

Value	Count	Frequency (%)
CREATE	158	34.4%
READ	136	29.6%
UPDATE	111	24.2%
DELETE	54	11.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
create	158	34.4%
read	136	29.6%
update	111	24.2%
delete	54	11.8%

Most occurring characters

Value	Count	Frequency (%)
E	725	29.2%
A	405	16.3%
T	323	13.0%
D	301	12.1%
R	294	11.8%
C	158	6.4%
U	111	4.5%
P	111	4.5%
L	54	2.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2482	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
E	725	29.2%
A	405	16.3%
T	323	13.0%
D	301	12.1%
R	294	11.8%
C	158	6.4%
U	111	4.5%
P	111	4.5%
L	54	2.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2482	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
E	725	29.2%
A	405	16.3%
T	323	13.0%
D	301	12.1%
R	294	11.8%
C	158	6.4%
U	111	4.5%
P	111	4.5%
L	54	2.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2482	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
E	725	29.2%
A	405	16.3%
T	323	13.0%
D	301	12.1%
R	294	11.8%
C	158	6.4%
U	111	4.5%
P	111	4.5%
L	54	2.2%

total_attributes
Real number (ℝ)

High correlation Zeros

Distinct	7
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.2766885

Minimum	0
Maximum	7
Zeros	109
Zeros (%)	23.7%
Negative	0
Negative (%)	0.0%
Memory size	3.7 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	2
95-th percentile	3
Maximum	7
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.99984777
Coefficient of variation (CV)	0.78315721
Kurtosis	2.6774864
Mean	1.2766885
Median Absolute Deviation (MAD)	1
Skewness	0.92414809
Sum	586
Variance	0.99969556
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
1	161	35.1%
2	160	34.9%
0	109	23.7%
3	17	3.7%
4	8	1.7%
5	3	0.7%
7	1	0.2%

Value	Count	Frequency (%)
0	109	23.7%
1	161	35.1%
2	160	34.9%
3	17	3.7%
4	8	1.7%
5	3	0.7%
7	1	0.2%

Value	Count	Frequency (%)
7	1	0.2%
5	3	0.7%
4	8	1.7%
3	17	3.7%
2	160	34.9%
1	161	35.1%
0	109	23.7%

intent_similarity
Categorical

High correlation Imbalance

Distinct	4
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	28.0 KiB

100.0	438
50.0	10
19.999999999999996	9
60.0	2

Length

Max length	18
Median length	5
Mean length	5.2287582
Min length	4

Characters and Unicode

Total characters	2400
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	100.0
2nd row	100.0
3rd row	100.0
4th row	100.0
5th row	100.0

Common Values

Value	Count	Frequency (%)
100.0	438	95.4%
50.0	10	2.2%
19.999999999999996	9	2.0%
60.0	2	0.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
100.0	438	95.4%
50.0	10	2.2%
19.999999999999996	9	2.0%
60.0	2	0.4%

Most occurring characters

Value	Count	Frequency (%)
0	1338	55.8%
.	459	19.1%
1	447	18.6%
9	135	5.6%
6	11	0.5%
5	10	0.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2400	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	1338	55.8%
.	459	19.1%
1	447	18.6%
9	135	5.6%
6	11	0.5%
5	10	0.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2400	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	1338	55.8%
.	459	19.1%
1	447	18.6%
9	135	5.6%
6	11	0.5%
5	10	0.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2400	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	1338	55.8%
.	459	19.1%
1	447	18.6%
9	135	5.6%
6	11	0.5%
5	10	0.4%

entity_similarity
Real number (ℝ)

Zeros

Distinct	27
Distinct (%)	5.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	90.231687

Minimum	0
Maximum	100
Zeros	12
Zeros (%)	2.6%
Negative	0
Negative (%)	0.0%
Memory size	3.7 KiB

Quantile statistics

Minimum	0
5-th percentile	22.222222
Q1	93.333333
median	100
Q3	100
95-th percentile	100
Maximum	100
Range	100
Interquartile range (IQR)	6.6666667

Descriptive statistics

Standard deviation	24.365125
Coefficient of variation (CV)	0.27002848
Kurtosis	5.6882098
Mean	90.231687
Median Absolute Deviation (MAD)	0
Skewness	-2.6469721
Sum	41416.344
Variance	593.65931
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
100	340	74.1%
93.33333333	50	10.9%
0	12	2.6%
22.22222222	9	2.0%
75	6	1.3%
66.66666667	6	1.3%
18.18181818	4	0.9%
36.36363636	3	0.7%
25	3	0.7%
46.15384615	3	0.7%
Other values (17)	23	5.0%

Value	Count	Frequency (%)
0	12	2.6%
14.28571429	1	0.2%
16.66666667	1	0.2%
18.18181818	4	0.9%
20	2	0.4%
22.22222222	9	2.0%
23.07692308	1	0.2%
25	3	0.7%
28.57142857	1	0.2%
29.26829268	1	0.2%

Value	Count	Frequency (%)
100	340	74.1%
94.11764706	2	0.4%
93.33333333	50	10.9%
92.30769231	1	0.2%
90.90909091	2	0.4%
88.88888889	3	0.7%
85.71428571	1	0.2%
75	6	1.3%
73.68421053	1	0.2%
66.66666667	6	1.3%

attributes_similarity
Real number (ℝ)

High correlation

Distinct	153
Distinct (%)	33.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	80.80638

Minimum	7.8431373
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 KiB

Quantile statistics

Minimum	7.8431373
5-th percentile	16.6
Q1	69.742063
median	100
Q3	100
95-th percentile	100
Maximum	100
Range	92.156863
Interquartile range (IQR)	30.257937

Descriptive statistics

Standard deviation	28.379442
Coefficient of variation (CV)	0.35120299
Kurtosis	0.48403822
Mean	80.80638
Median Absolute Deviation (MAD)	0
Skewness	-1.3557104
Sum	37090.128
Variance	805.39274
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	244	53.2%
22.22222222	18	3.9%
12.5	4	0.9%
66.66666667	4	0.9%
16	4	0.9%
95.23809524	4	0.9%
26.66666667	4	0.9%
16.66666667	3	0.7%
67.74193548	3	0.7%
95.83333333	3	0.7%
Other values (143)	168	36.6%

Value	Count	Frequency (%)
7.843137255	2	0.4%
8.333333333	1	0.2%
9.756097561	1	0.2%
10.52631579	1	0.2%
10.81081081	2	0.4%
11.42857143	2	0.4%
12.12121212	1	0.2%
12.5	4	0.9%
13.33333333	1	0.2%
13.79310345	2	0.4%

Value	Count	Frequency (%)
100	244	53.2%
99.29078014	1	0.2%
98.27586207	1	0.2%
97.77777778	2	0.4%
97.56097561	1	0.2%
97.5	1	0.2%
97.48743719	1	0.2%
97.2972973	1	0.2%
96.96969697	1	0.2%
96.77419355	1	0.2%

filters_similarity
Real number (ℝ)

High correlation

Distinct	104
Distinct (%)	22.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	80.034335

Minimum	3.7735849
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 KiB

Quantile statistics

Minimum	3.7735849
5-th percentile	22.105263
Q1	57.894737
median	100
Q3	100
95-th percentile	100
Maximum	100
Range	96.226415
Interquartile range (IQR)	42.105263

Descriptive statistics

Standard deviation	30.070405
Coefficient of variation (CV)	0.37571881
Kurtosis	-0.2980088
Mean	80.034335
Median Absolute Deviation (MAD)	0
Skewness	-1.1360756
Sum	36735.76
Variance	904.22927
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	284	61.9%
22.22222222	22	4.8%
57.89473684	10	2.2%
95	9	2.0%
25	6	1.3%
28.57142857	4	0.9%
26.66666667	4	0.9%
20	3	0.7%
19.04761905	3	0.7%
23.52941176	3	0.7%
Other values (94)	111	24.2%

Value	Count	Frequency (%)
3.773584906	1	0.2%
5.263157895	1	0.2%
5.333333333	1	0.2%
6.666666667	1	0.2%
7.272727273	1	0.2%
8.888888889	1	0.2%
10.81081081	1	0.2%
11.05990783	1	0.2%
11.42857143	1	0.2%
11.88118812	1	0.2%

Value	Count	Frequency (%)
100	284	61.9%
96.77419355	1	0.2%
95.65217391	1	0.2%
95.45454545	1	0.2%
95.23809524	1	0.2%
95	9	2.0%
94.44444444	1	0.2%
94.11764706	1	0.2%
92.68292683	1	0.2%
92.30769231	1	0.2%

similarity_media
Real number (ℝ)

High correlation

Distinct	255
Distinct (%)	55.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	87.060039

Minimum	24.479432
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 KiB

Quantile statistics

Minimum	24.479432
5-th percentile	57.688021
Q1	78.347393
median	93.75
Q3	98.913043
95-th percentile	100
Maximum	100
Range	75.520568
Interquartile range (IQR)	20.56565

Descriptive statistics

Standard deviation	14.838294
Coefficient of variation (CV)	0.17043748
Kurtosis	0.69573559
Mean	87.060039
Median Absolute Deviation (MAD)	6.25
Skewness	-1.1767138
Sum	39960.558
Variance	220.17497
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	98	21.4%
98.33333333	36	7.8%
80.55555556	21	4.6%
70.02923977	10	2.2%
93.75	7	1.5%
98.80952381	4	0.9%
91.66666667	3	0.7%
92	3	0.7%
98.95833333	3	0.7%
81.25	3	0.7%
Other values (245)	271	59.0%

Value	Count	Frequency (%)
24.47943226	1	0.2%
40.35421785	1	0.2%
41.25481386	1	0.2%
41.46491228	1	0.2%
42.88386212	1	0.2%
43.17144863	1	0.2%
43.95833333	1	0.2%
46.75830705	1	0.2%
49.52380952	2	0.4%
49.571949	1	0.2%

Value	Count	Frequency (%)
100	98	21.4%
99.82269504	1	0.2%
99.56896552	1	0.2%
99.44444444	2	0.4%
99.3902439	1	0.2%
99.375	1	0.2%
99.3718593	1	0.2%
99.32432432	1	0.2%
99.24242424	1	0.2%
99.19354839	1	0.2%

	attributes_similarity	entity_similarity	expected_class	expected_intent	filters_similarity	find_intent	intent_similarity	similarity_media	total_attributes
attributes_similarity	1.000	-0.118	0.071	0.461	0.148	0.449	0.197	0.576	-0.627
entity_similarity	-0.118	1.000	0.362	0.132	0.011	0.131	0.000	0.310	0.270
expected_class	0.071	0.362	1.000	0.332	0.000	0.308	0.294	0.099	0.319
expected_intent	0.461	0.132	0.332	1.000	0.396	0.932	0.142	0.273	0.559
filters_similarity	0.148	0.011	0.000	0.396	1.000	0.419	0.480	0.718	0.039
find_intent	0.449	0.131	0.308	0.932	0.419	1.000	0.162	0.314	0.531
intent_similarity	0.197	0.000	0.294	0.142	0.480	0.162	1.000	0.536	0.038
similarity_media	0.576	0.310	0.099	0.273	0.718	0.314	0.536	1.000	-0.148
total_attributes	-0.627	0.270	0.319	0.559	0.039	0.531	0.038	-0.148	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

	user_msg	expected_intent	expected_class	expected_attributes	expected_filter_attributes	processed_attributes	processed_filters	find_entity	find_intent	total_attributes	intent_similarity	entity_similarity	attributes_similarity	filters_similarity	similarity_media
0	add student with name=anderson martins gomes, age=20	CREATE	student	{'name': 'anderson martins gomes', 'age': '20'}	{}	{'name': 'anderson martins gomes', 'age': '20'}	{}	student	CREATE	2	100.0	100.000000	100.000000	100.000000	100.000000
1	add subject with name=brazilian history, description=the history of brazil	CREATE	subject	{'name': 'brazilian history', 'description': 'the history of brazil'}	{}	{'name': 'brazilian history', 'history': 'history of'}	{}	subject	CREATE	2	100.0	100.000000	81.300813	100.000000	95.325203
2	add teacher with name=paulo henrique, age=65, email=ph@uece.br	CREATE	teacher	{'name': 'paulo henrique', 'age': '65', 'email': 'ph@uece.br'}	{}	{'name': 'paulo henrique', 'age': '65', 'email': 'ph@uecebr', '.': 'br'}	{}	teacher	CREATE	3	100.0	100.000000	92.537313	100.000000	98.134328
3	add subject with name=math, description=the best subject ever	CREATE	subject	{'name': 'math', 'description': 'the best subject ever'}	{}	{'name': 'math', 'description': 'the best subject ever'}	{}	subject	CREATE	2	100.0	100.000000	100.000000	100.000000	100.000000
4	add subject with name=math, description='the best subject ever!'	CREATE	subject	{'name': 'math', 'description': 'the best subject ever!'}	{}	{'name': 'math', 'description': "'the best subject ever!'"}	{}	subject	CREATE	2	100.0	100.000000	98.275862	100.000000	99.568966
5	add student name=anderson	CREATE	student	{'name': 'anderson'}	{}	{'name': 'anderson'}	{}	student	CREATE	1	100.0	100.000000	100.000000	100.000000	100.000000
6	get students with name anderson	READ	student	{}	{'name': 'anderson'}	{}	{'name': 'anderson'}	students	READ	1	100.0	93.333333	100.000000	100.000000	98.333333
7	show me the teachers	READ	teacher	{}	{}	{}	{}	teachers	READ	0	100.0	93.333333	100.000000	100.000000	98.333333
8	show teachers	READ	teacher	{}	{}	{}	{}	teachers	READ	0	100.0	93.333333	100.000000	100.000000	98.333333
9	show teacher	READ	teacher	{}	{}	{}	{'teacher': ''}	show	READ	0	100.0	18.181818	100.000000	23.529412	60.427807

	user_msg	expected_intent	expected_class	expected_attributes	expected_filter_attributes	processed_attributes	processed_filters	find_entity	find_intent	total_attributes	intent_similarity	entity_similarity	attributes_similarity	filters_similarity	similarity_media
449	update article with id=12, setting revision=1	UPDATE	article	{'revision': '1'}	{'id': '12'}	{'revision': '1'}	{'id': '12'}	article	UPDATE	2	100.0	100.000000	100.000000	100.000000	100.000000
450	add a movie with title='batman begins'	CREATE	film	{'title': 'batman begins'}	{}	{'title': "'batman begins'"}	{}	movie	CREATE	1	100.0	22.222222	96.296296	100.000000	79.629630
451	add a movie with title='the dark knight', "running time"=152	CREATE	film	{'title': 'the dark knight', 'running_time': '152'}	{}	{'title': "'the dark knight'", 'running': 'time"152'}	{}	movie	CREATE	2	100.0	22.222222	88.461538	100.000000	77.670940
452	get all students with name='anderson'	READ	student	{}	{'name': 'anderson'}	{}	{'students': "with name'anderson'", 'name': "'anderson'"}	a	READ	1	100.0	0.000000	100.000000	51.948052	62.987013
453	add a former teacher with name='onelia'	CREATE	former_teacher	{'name': 'onelia'}	{}	{'name': "'onelia'", 'onelia': "'"}	{}	teacher	CREATE	1	100.0	66.666667	67.924528	100.000000	83.647799
454	add an invoice with value=100	CREATE	invoice	{'value': '100'}	{}	{'value': '100'}	{}	invoice	CREATE	1	100.0	100.000000	100.000000	100.000000	100.000000
455	get all invoice	READ	invoice	{}	{}	{}	{}	invoice	READ	0	100.0	100.000000	100.000000	100.000000	100.000000
456	add car with license=2020	CREATE	car	{'license': '2020'}	{}	{'license': '2020'}	{}	car	CREATE	1	100.0	100.000000	100.000000	100.000000	100.000000
457	add car with color=black	CREATE	car	{'color': 'black'}	{}	{'color': 'black'}	{}	car	CREATE	1	100.0	100.000000	100.000000	100.000000	100.000000
458	get all cars	READ	car	{}	{}	{}	{}	cars	READ	0	100.0	85.714286	100.000000	100.000000	96.428571

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category